Oliver Diaz

Associate Professor at UB. He teachs several modules of the BSc in Computer Science, incIuding Computer Vision

Profile summary

Dr. Oliver Díaz is an Associate Professor at the Faculty of Mathematics and Computer Science at the University of Barcelona. He holds a PhD in Electronic Engineering from the University of Surrey, UK (2013) and was a Marie Skłodowska-Curie Fellow (2015-2017). He has 15 years international research experience in the field of medical imaging and medical physics, and has participated in 20+ research projects. Dr Díaz is member of several national and international working groups, board member at large of European Society of Medical Imaging Informatics (EuSoMII) or member of European Society of Radiology Imaging Biomarkers Alliance Subcommittee among other committees. His research’s interests include the use of Machine Learning / Artificial Intelligence tools applied to healthcare.

Latest publications

Oliver Diaz has 164 publications on Google Scholar.
Only the last 20 publications are shown here. Access Oliver Diaz Google Scholar Profile

Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

2026 | Nicholas Konz, Richard Osuala, Preeti Verma, Yuwen Chen, Hanxue Gu, Haoyu Dong, Yaqian Chen, Andrew Marshall, Lidia Garrucho, Kaisar Kushibar, Daniel M Lang, Gene S Kim, Lars J Grimm, John M Lewin, James S Duncan, Julia A Schnabel, Oliver Diaz, Karim Lekadir, Maciej A Mazurowski | Medical Image Analysis, 103943, 2026

Oliver Diaz

Profile summary

Latest publications

Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction

From data to treatment plan: An AI-driven path for automated breast radiotherapy planning

A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations

Evaluation metrics in medical imaging AI: fundamentals, pitfalls, misapplications, and recommendations

Simulating dynamic tumor contrast enhancement in breast MRI using conditional generative adversarial networks

Stakeholder engagement: the path to trustworthy AI in healthcare

Explanation and Elaboration with Examples for METRICS (METRICS-E3): an initiative from the EuSoMII Radiomics Auditing Group

Federated nnU-Net for privacy-preserving medical image segmentation

Breast radiotherapy planning: A decision‐making framework using deep learning

A review of methods for trustworthy AI in medical imaging: The FUTURE-AI Guidelines

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy

Development of Method to Predict Career Choice of IT Students in Kazakhstan by Applying Machine Learning Methods

Segmentation variability and radiomics stability for predicting Triple-Negative Breast Cancer subtype using Magnetic Resonance Imaging

Clinically-guided Data Synthesis for Laryngeal Lesion Detection

A Wearable Electronic Band for Stress Understanding Using Machine Learning

Optimization and validation of a mechanical compression model for digital breast phantoms in mammography and tomosynthesis simulations

Assessing Cancer Presence in Prostate MRI Using Multi-Encoder Cross-Attention Networks

Generating Synthetic Data in Cancer Research

Research lines

Artificial Intelligence applied to Health

Medical Imaging

Data Science & Bio-Medical Applications